This paper presents an interesting approach for computing the sentiment of movie aspects. The authors use dependency parsing to split sentences into independent clauses and then apply an extensive set of manually drafted sentiment calculation rules that leverage the sentence's part of speech tags to compute the per clause sentiment.

domain specific sentiment lexicon: (i) use the information gain measure to obtain opinion words that are strongly associated with positive or negative reviews; (ii) manual examination of the candidate sentiment terms and creation of the domain specific lexicon which comprises approximately 100 terms.

sentences are dependency parsed and then divided into independent clauses (i.e. sub-trees containing single statements).

computation of the clause sentiment based on calculation rules that consider the words' part of speech tags and negation.

aspect sentiment: the sentiment score for each review aspect is calculated by computing the average sentiment of all clauses in which terms referencing to that particular aspect are mentioned.

Evaluation

Experiments conducted on 1000 manually annotated sentences (and the corresponding movie aspects) indicate that the presented method yields very good results and clearly outperforms the baseline approaches. The authors also provide an error analysis which identifies the following error classes: